Research Outputs
An adaptive basin management rule to improve water allocation resilience under climate variability and change-A case study in the Laja lake basin in Southern Chile
Due to population growth and expansion in the agricultural and industrial sectors, the demand for water has increased. However, water availability in some regions has decreased due to climate change trends and variability, necessitating innovative strategies and adaptation in water allocation to avoid conflicts among users in a hydrological system. This paper presents a resilience analysis and a conceptual hydrological modeling approach to evaluate the resilience capacity of a new water allocation rule in the Laja Lake basin in southern Chile. Resilience assessments included absorptive and adaptive capacities with four system states: resilient, susceptible, resistant, and vulnerable. A modeling approach was used considering the climate variability uncertainty and climate change trends of the Laja system. Characterization of adaptive and absorptive capacities showed that the Laja Lake basin moved from resistant to vulnerable. Hydrological modeling analyses showed that after a new water allocation agreement, the Laja Lake system is moving from vulnerable to susceptible, since the new rule has more adaptive alternatives to face climate variability. The new rule diminishes the possibilities of conflicts among users, ensuring the fulfillment of water needs for uses such as farming and ecosystem services such as landscaping, and allows for increased water allocation for energy in wet hydrological years.
Integration of Slurry–Total Reflection X-ray fluorescence and machine learning for monitoring arsenic and lead contamination: Case study in Itata valley agricultural soils, Chile
The accuracy of determining arsenic and lead using the optical technique Slurry–Total Reflection X-ray Fluorescence (Slurry-TXRF) was significantly enhanced through the application of a machine learning method, aimed at improving the ecological risk assessment of agricultural soils. The overlapping of the arsenic Kα signal at 10.55 keV with the lead Lα signal at 10.54 keV due to the relatively low resolution of TXRF could compromise the determination of lead. However, by applying a Partial Least Squares (PLS) machine learning algorithm, we mitigated interference variations, resulting in improved selectivity and accuracy. Specifically, the average percentage error was reduced from 15.6% to 9.4% for arsenic (RMSEP improved from 5.6 mg kg−1 to 3.3 mg kg−1) and from 18.9% to 6.8% for lead (RMSEP improved from 12.3 mg kg−1 to 5.03 mg kg−1) compared to the previous univariable model. This enhanced predictive accuracy, within the set of samples concentration range, is attributable to the efficiency of the multivariate calibration first-order advantage in quantifying the presence of interferents. The evaluation of X-ray fluorescence emission signals for 26 different synthetic calibration mixtures confirmed these improvements, overcoming spectral interferences. Additionally, the application of these models enabled the quantification of arsenic and lead in soils from a viticultural subregion of Chile, facilitating the estimation of ecological risk indices in a fast and reliable manner. The results indicate that the contamination level of these soils with arsenic and lead ranges from moderate to considerable.
Remote sensing with UAVs for flood modeling: A validation with actual flood records
The use of unmanned aerial vehicles (UAVs) is steadily increasing due to their capacity to capture terrain elevation data with remarkable precision and cost-effectiveness. Nonetheless, their application for estimating water surface elevations and submerged terrain, such as channel bathymetry, remains constrained. Consequently, the development of a digital terrain model that relies on UAV data during low-water periods assumes a more extensive dry channel surface area, thus alleviating the information gap regarding submerged terrain. The objective of this brief report is to validate a hydraulic model for flood calculation. To this end, a 1D steady-state hydrological model of the Ñuble River based on a UAV survey in the low-water period of 2016 was constructed in HEC-RAS v.5.0.3 and compared to water surface elevation observations of the flood on 24 June 2023. The model tends to overestimate the flood, but the errors are considered tolerable for flood calculation (on average, a 10.6% depth error was obtained for a 30-year return period flood); therefore, the hydraulic model derived from remote sensing seems to be an effective alternative for the construction of hydraulic models for flood studies.
Estimating the optimal velocity measurement time in rivers’ flow measurements: An uncertainty approach
The gauging process can be very extensive and time-consuming due to the procedures involved. Since velocity measurement time (VMT) is one of the main variables that would allow gauging times to be reduced, this study seeks to determine the optimal point VMT and, thereby, reduce the overall gauging time. An uncertainty approach based on the USGS area-velocity method and the GLUE methodology applied to eight gauging samples taken in shallow rivers located in South-central Chile was used. The average point velocity was calculated as the average of 1 to 70 randomly selected instant velocity samples (taken every one second). The time at which the uncertainty bands reached a stability criterion (according to both width and slope stability) was considered to be the optimum VMT since the variations were negligible and it does not further contribute to a less uncertain solution. Based on the results, it is concluded that the optimum point VMT is 17 s. Therefore, a point velocity measurement of 20 s is recommended as the optimal time for gauging in shallow rivers.
Estimation of annual maximum and minimum flow trends in a data-scarce basin. Case study of the Allipén river watershed, Chile
Data on historical extreme events provides information not only for water resources planning and management but also for the design of disaster-prevention measures. However, most basins around the globe lack long-term hydro-meteorological information to derive the trend of hydrological extremes. This study aims to investigate a method to estimate maximum and minimum flow trends in basins with limited streamflow records. To carry out this study, data from the Allipén River watershed (Chile), the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological model at a daily time step, and an uncertainty analysis were used. Through a calibration using only five years of records, 21-year mean daily flow series were generated and the extreme values derived. To analyze the effect of the length of data availability, 2, 5, and 10 years of flows were eliminated from the analyses. The results show that in the case of 11 years of simulated flows, the annual maximum and minimum flow trends present greater uncertainty than in the cases of 16 and 19 years of simulated flows. Simulating 16 years, however, proved to properly simulate the observed long-term trends. Therefore, in data-scarce areas, the use of a hydrological model to simulate extreme mean daily flows and estimate long-term trends with at least 16 years of meteorological data could be a valid option.
Identifying a minimum time period of streamflow recession records to analyze the behavior of groundwater storage systems: A study in heterogeneous Chilean watersheds
Aquifers are complex systems that present significant challenges in terms of characterization due to the lack or absence of watershed-scale hydrogeological information. An alternative to address the need to characterize watershed-scale aquifer behavior is recession flow analysis. Recession flows are flows sustained by groundwater release from the aquifer. Aquifer behavior can be characterized using recession flow records available from gauging stations, and therefore an indirect measure of aquifer behavior is obtained through watershed-scale recession flow records and analysis. This study seeks to identify the minimum time period necessary to characterize the behavior of groundwater storage systems in watersheds with different geological, morphological, and hydrological characteristics. To this end, various watersheds in south-central Chile underwent recession flow analysis, with eight time periods considered (2, 3, 4, 5, 10, 15, 20, and 25 years). The results indicate that 25 years of records are sufficient for the characterization of watershed-scale aquifer behavior, along with the representation of the groundwater storage-release (S-Q) process in watersheds with different geological, morphological, and hydrological characteristics. Additionally, the results show that an initial characterization of the groundwater system behavior in watersheds with different geological characteristics can be carried out with two years of records. This information could be important for practical engineering and the study of groundwater systems in watersheds with limited hydrological and hydrogeological information.
Remote sensing with UAVs for modeling floods: An exploratory approach based on three Chilean rivers
The use of unmanned aerial vehicles (UAVs) has been steadily increasing due to their ability to acquire high-precision ground elevation information at a low cost. However, these devices have limitations in estimating elevations of the water surface and submerged terrain (i.e., channel bathymetry). Therefore, the creation of a digital terrain model (DTM) using UAVs in low-water periods means a greater dry channel surface area and thus reduces the lack of information on the wet area not appropriately measured by the UAV. Under such scenarios, UAV-DTM-derived data present an opportunity for practical engineering in estimating floods; however, the accuracy of estimations against current methods of flood estimations and design needs to be measured. The objective of this study is therefore to develop an exploratory analysis for the creation of hydraulic models of river floods using only UAV-derived topographic information. Hydraulic models were constructed based on DTMs created in (i) the traditional manner, considering the bathymetry measured with RTK-GPS and topography, and via (ii) remote sensing, which involves topography measurement with a UAV and assumes a flat bed in the part of the channel covered by water. The 1D steady-state HEC-RAS model v.5.0.3 was used to simulate floods at different return periods. The applied methodology allows a slightly conservative, efficient, economical, and safe approach for the estimation of floods in rivers, with an RMSE of 6.1, 11.8 and 12.6 cm for the Nicodahue, Bellavista and Curanilahue rivers. The approach has important implications for flood studies, as larger areas can be surveyed, and cost-and time-efficient flood estimations can be performed using affordable UAVs. Further research on this topic is necessary to estimate the limitations and precision in rivers with different morphologies and under different geographical contexts.
Analysis of the behavior of groundwater storage systems at different time scales in basins of South Central Chile: A study based on flow recession records
Understanding the groundwater storage and release (S-Q) process and its contribution to river flows is essential for different hydrological applications, especially in periods of water scarcity. The S-Q process can be characterized based on recession parameter b, which is the slope of the power–law relationship −dQ/dt = aQb of the recession flow analysis, where recession parameter b represents the linearity of the S-Q process. In various studies, it has been found that this parameter can present high variability, which has been associated with the approach or spatial variability of basin characteristics. However, the variability of parameter b and its relationship with geology and the behavior of groundwater storage over time (evolution over time) have not been sufficiently studied. The objective of this study is to analyze the variability of recession parameter b and its relationship with geological and morphological characteristics and climate variability at different time scales. To this end, 72 drainage basins located in south central Chile were examined via recession flow analysis, considering five different time scales (5 years, 10 years, 15 years, 20 years, and 25 years). In addition, to analyze spatial variability patterns and generate groups of basins with similar characteristics, a cluster analysis was carried out. Clusters were obtained using the principal component analysis (PCA) and K-means methods. The results show that in wet periods, the slope of recession parameter b tends to increase (fast drainage process), while in dry periods, the recession slope tends to decrease (slow drainage processes). In general, the results suggest that the variability of recession coefficient b indicates changes in S-Q behavior; therefore, it could be used as an indicator of the sensitivity of a basin to climate variability.
Unraveling complex hydrogeological processes in Andean basins in south‐central Chile: An integrated assessment to understand hydrological dissimilarity
Groundwater storage, drainage, and interbasin water exchange are common hydrological processes but often difficult to quantify due to a lack of local observations. We present a study of three volcanic mountainous watersheds located in south‐central Chile (~36.9 ° S) in the Chillán volcanic complex (Chillán, Renegado, and Diguillín river basins). These are neighboring basins that are similar with respect to the metrics normally available for characterization everywhere (e.g., precipitation, temperature, and land cover). In a hydrological sense, similar (proportional) behavior would be expected if these catchments would be characterized with this general information. However, these watersheds show dissimilar behavior when analyzed in detail. The surface water balance does not fit for any of these watersheds individually; however, the water balance of the whole system can be explained by likely interbasin water exchanges. The Renegado river basin has an average annual runoff per unit of area on the order of 60–65% less than those of the Diguillín and Chillán rivers, which is contradictory to the hydrological similarity among the basins. To understand the main processes that control streamflow generation, two analyses were performed: (a) basin metrics (land cover, geologic, topographic, and climatological maps) and hydro‐meteorological data analyses and (b) a water balance model approach. The analyses contribute to a plausible explanation for the hydrogeological processes in the system. The soils, topography, and geology of the Chillán–Renegado–Diguillín system favor the infiltration and groundwater movements from the Renegado river basin, mainly to the neighboring Diguillín basin. The interbasin water exchanges affect hydrological similarity and explain the differences observed in the hydrological processes of these three apparently similar volcanic basins. The results highlight the complexity of hydrological processes in volcanic mountainous systems and suggest that a simple watershed classification approach based on widely available data is insufficient. Simple local analyses such as specific flow analysis with a review of the geology and morphology can contribute to a better understanding of the hydrology of volcanic mountainous areas.
A sensitivity analysis approach for assessing the effect of design parameters in reducing seismic demand of Base-Isolated storage racks
The most used global sensitivity analysis (GSA) method is based on variance. This is performed using Monte Carlo Sampling (MCS) or Latin Hypercube Sampling (LHS). It requires a large sample to obtain accurate estimates. Density-based methods, such as the GSA PAWN, have been developed to reduce the sample size without compromising the result. PAWN is simpler than other methods because it uses cumulative density functions (CDF) instead of probability density. This method has been widely used in areas such as environmental engineering with very good results, reducing computation time. However, its use in structural engineering is incipient. The PAWN method was used to classify the design variables of the isolation system in relation to their sensitivity, and in relation to the seismic response of industrial storage racks. The above was analyzed in terms of the effectiveness of each variable to reduce the seismic demand using a novel base isolation kinematic device (BIKD). Racks with different combinations of their structural parameters such as the number of storage levels, the height between them, and isolation period, among others, were studied. The dimensions of the racks were chosen to match those that would later be experimentally tested on shaking table. An earthquake whose response spectrum matched the design spectrum of current Chilean regulations, was considered as seismic forcing. The maximum base shear load, the displacement of the top level of storage and the floor drift were considered as target responses to be studied. Fixed base racks (FBR), as reference, and base-isolated racks (BIR) were analyzed. The results showed the effectiveness of using the BIKD system in reducing all three-target responses up to one order of magnitude. Additionally, it was determined that the parameters that have the greatest influence on the response correspond to the number of storage levels and the height between them, both for FBR and BIR.